LOGISTICS (3 Credits)
Learning Outcomes: At the end of this course, students will be able to: Explain the model for industrial logistics problems of its objectives, constraints and decision variables; Design logistics sys...
Learning Outcomes: At the end of this course, students will be able to: Explain the model for industrial logistics problems of its objectives, constraints and decision variables; Design logistics sys...
Learning Outcomes: Upon successful completion of this course, students are expected to be able to: identify logistics operational problems and issues in business organizations; assess and build innov...
Learning Outcomes: On successful completion of this course, students will be able to: Explain the concept of machine learning; Apply skill of knowledge data discovery to be used in different variety ...
Learning Outcomes On successful completion of this Course, students will be able to: Develop a comprehensive understanding of concepts, techniques and algorithms of machine learning in the supervised...
Learning Outcomes : On successful completion of this course, student will be able to: Explain the fundamental of machine learning concept; Interpret the distribution of dataset using regression metho...
Learning Outcomes: On successful completion of this course, student will be able to: Explain game development in Unity Programming; Apply techniques in 2D and 3D game programming; design User Interfa...
Learning Outcomes: On successful completion of this course, student will be able to: Explain concepts and challenges of machine learning systems Demonstrate feature engineering techniques on ...
Learning Outcomes: On successful completion of this course, students will be able to: explain concepts and challenges of machine learning systems; demonstrate feature engineering techniques on th...
Learning Outcomes: On successful completion of this course, students will be able to: LO1 - differentiate between traditional deterministic software and probabilistic machine learning systems, identi...
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